A Behavioral Lifestyle Intervention to Improve Frailty in Overweight or Obese Older Adults with Type 2 Diabetes: A Feasibility Study

Feasibility and preliminary efficacy of different intensities of functional training in elderly type 2 diabetes patients with cognitive impairment: a pilot randomised controlled trial

BACKGROUND

Aging and type-2 diabetes (T2D) are the most important risk factors for cognitive impairment and Alzheimer's disease. Exercise training is an effective, safe, and practical intervention in improving glucose metabolism, physical function, and cognitive disorders. This pilot study investigated the feasibility and preliminary efficacy of high-intensity low-volume (HIFT) vs. low-intensity high-volume (LIFT) functional training in elderly T2D patients with cognitive impairment.

METHODS

Forty-eight elderly T2D patients (31 female, 17 male, age 67.5 ± 5.8 years, MMSE score 18.8 ± 2.6, FBG 209.5 ± 37.9) were randomly assigned to HIFT, LIFT and control groups. Cognitive impairment was diagnosed with MMSE ≤ 23 based Iranian society. The SDMT, CVLT-II, BVMT-R, and Stroop tests were used to evaluated processing speed, learning, memory and attention respectively. Physical fitness tests include: tandem stance and walk test; TUG; 6MWT, 10MWT; SSST; 5TSTS; and hand grip was used to evaluated static and dynamic balance, agility, walking endurance, gait speed, lower limb function and lower and upper body strength respectively. As well as, Biochemical (FBG, insulin, HOMA-IR, HbA1c) and physiological outcomes (SBP, and DBP) were assessed. The HIFT group performed six weeks of functional training (three sessions per week) with 120-125% of the lactate threshold. The LIFT group performed six weeks of functional training (five sessions per week) with a 70-75% lactate threshold. Feasibility, safety, and acceptability of exercise programs were assessed at the end of the study.

RESULT

HIFT showed a higher adherence rate (91% vs. 87.5%), safety, and acceptability compared to LIFT. MMSE and Stroop scores, 6MWT, FBG, insulin, HOMA-IR, HbA1c, SBP, and DBP significantly improved in HIFT (all, P ≤ 0.004) and LIFT (all, P ≤ 0.023). Changes in 6MWT, FBG, insulin, HOMA-IR, and HbA1c in HIFT (all, P ≤ 0.001) and LIFT (all, P ≤ 0.008) were significant compared to the control group. Changes in Stroop scores were significant only in the HIFT group compared to the control group (P = 0.013). SDMT, CVLT-II, BVMT-R, balance test, 10MWT, SSST, TUG and hang grip significantly improved only in HIFT (all, P ≤ 0.038).

CONCLUSION

HIFT vs. LIFT is a safe, feasible, and effective approach for improving some aspects of physical, biochemical, and cognitive function in elderly T2D patients with cognitive impairment. This pilot study provides initial proof-of-concept data for the design and implementation of an appropriately powered randomised controlled trial (RCT) of HIFT vs. LIFT in a larger sample of elderly T2D patients with cognitive impairment.

TRIAL REGISTRATION

Randomized controlled trial (RCT) (Iranian Registry of Clinical Trials, trial registration number: IRCT20230502058055N1. Date of registration: 11/06/2023.

RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) Evaluation of the Use of Activity Trackers in the Clinical Care of Adults Diagnosed With a Chronic Disease: Integrative Systematic Review

BACKGROUND

Chronic diseases are a leading cause of adult mortality, accounting for 41 million deaths globally each year. Low levels of physical activity and sedentary behavior are major risk factors for adults to develop a chronic disease. Physical activity interventions can help support patients in clinical care to be more active. Commercial activity trackers that can measure daily steps, physical activity intensity, sedentary behavior, and distance moved are being more frequently used within health-related interventions. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework is a planning and evaluation approach to explore the reach, effectiveness, adoption, implementation, and maintenance of interventions.

OBJECTIVE

The objective of this study is to conduct an integrative systematic review and report the 5 main RE-AIM dimensions in interventions that used activity trackers in clinical care to improve physical activity or reduce sedentary behavior in adults diagnosed with chronic diseases.

METHODS

A search strategy and study protocol were developed and registered on the PROSPERO platform. Inclusion criteria included adults (18 years and older) diagnosed with a chronic disease and have used an activity tracker within their clinical care. Searches of 10 databases and gray literature were conducted, and qualitative, quantitative, and mixed methods studies were included. Screening was undertaken by more than 1 researcher to reduce the risk of bias. After screening, the final studies were analyzed using a RE-AIM framework data extraction evaluation tool. This tool assisted in identifying the 28 RE-AIM indicators within the studies and linked them to the 5 main RE-AIM dimensions.

RESULTS

The initial search identified 4585 potential studies. After a title and abstract review followed by full-text screening, 15 studies were identified for data extraction. The analysis of the extracted data found that the RE-AIM dimensions of adoption (n=1, 7% of studies) and maintenance (n=2, 13% of studies) were underreported. The use of qualitative thematic analysis to understand the individual RE-AIM dimensions was also underreported and only used in 3 of the studies. Two studies used qualitative analysis to explore the effectiveness of the project, while 1 study used thematic analysis to understand the implementation of an intervention.

CONCLUSIONS

Further research is required in the use of activity trackers to support patients to lead a more active lifestyle. Such studies should consider using the RE-AIM framework at the planning stage with a greater focus on the dimensions of adoption and maintenance and using qualitative methods to understand the main RE-AIM dimensions within their design. These results should form the basis for establishing long-term interventions in clinical care.

TRIAL REGISTRATION

PROSPERO CRD42022319635; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=319635.

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework

BACKGROUND

Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

OBJECTIVE

Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

METHODS

MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

RESULTS

In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

CONCLUSIONS

This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.